Assistive glove for Pakistani Sign Language translation

Abstract

This paper presents system to translate gestures of Urdu Sign language using an instrumented wearable glove. This system contributes first ever attempt in terms of fabrication of Pakistani Sign Language translating glove which is portable as well as cost effective. As the sensor values from the glove vary from person to person, this system was made to use pattern recognition approach. In order to accomplish the task, Principal Component Analysis (PCA) was employed for feature extraction and Euclidean distance as classification technique. Up till now the system has ten static gestures in its library and it perfectly judges nine gestures out of targeted ten gestures which are commonly used in Urdu Sign language.

A Review on Systems-Based Sensory Gloves for Sign Language Recognition State of the Art between 2007 and 2017

“…These optical sensors were used to capture finger tilt and the LSM330DLC chip; 3-axis ACC and 3-axis gyroscope were used to determine hand motion. A translator system was presented to interpret Urdu SL gestures by using a wearable data glove [ 6 ]. Five flex sensors of 4.5-inches in length were placed on each finger, and an accelerometer MMA 7361 (SparkFun Electronics, Niwot, CO, USA), was placed on the palm.…”

“…Several Arduino boards are available on the market such as Arduino Nano, Uno, Mega, etc. ; for instance, Arduino Uno (Arduino, Italy), ( Figure 13 c) is based on the ATmega328P microcontroller and has 14 digital inputs/outputs, 6 analog inputs, a 16 MHz quartz crystal, and USB connection [ 6 , 8 , 21 , 37 , 56 , 57 , 58 , 59 ]. Odroid XU4 (Hardkernel2, Anyang, South Korea) ( Figure 13 d), produced by Hardkernel2, uses a Samsung Exynos5 Octa 5410 processor that consists of 4 CPU cores each with Cortex™-A15 cores; it was used for the development of the data glove [ 59 ].…”

“…The main device adopted by researchers as the output was the screen of computer [ 3 , 4 , 35 , 40 , 48 , 60 , 61 , 62 ]. Other devices attracting the attention of researchers are the liquid-crystal display (LCD) [ 12 , 35 , 57 , 63 ], speaker [ 38 , 46 , 54 , 64 ], or both [ 6 , 51 , 55 , 65 , 66 , 67 , 68 ]. Ultimately, the smartphone is another alternative chosen for system output [ 9 , 42 , 48 , 59 , 69 ].…”

“…The attention given to the sensory glove is due to its capability to capture the data required to photograph the shape and movement of the hand for the purpose of recognizing the gestures of SL. Despite the fact that SL has plenty of postures, many studies have concentrated on a selective set of postures that may be as small as some letters of the alphabet [ 21 , 44 , 47 , 51 , 78 ]; or the postures of the most frequently used words [ 37 , 41 , 45 , 55 , 56 , 72 , 77 , 79 ]; or a combination of the alphabet, numbers, and words [ 6 ] to perform their experiments and develop an SLR system. Others have contributed to the expansion of the database of gestures allocated for the purpose of developing a system to distinguish them and make them include either whole alphabets [ 4 , 11 , 35 , 46 , 50 , 57 , 64 , 65 , 70 ], numbers within the range 0 to 9 [ 10 ], or both, in the same system [ 39 , 42 , 69 ].…”

“…This can be achieved by developing a glove equipped with sensors and an electronic circuit. Several benefits of using this device are that no complex data processing is needed [ 4 ]; there are no limitations on movements such as sitting behind a desk or chair; hand shape recognition is not affected by the background condition [ 5 , 6 ]; it is a lightweight, SLR-based glove device that can be carried to make mobility easy and comfortable [ 7 , 8 ]; and it is a recognition system that can be employed for learning SL for both dumb and able people [ 9 ]. Furthermore, numerous kinds of applications are currently involved in gesture recognition systems such as SLR, substitutional computer interfaces, socially assistive robotics, immersive gaming, virtual objects, remote control, medicine-health care, gesture recognition of hand/body language, etc.…”